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A GEOGRAPHIC SAMPLING STRATEGY FOR STUDYING RELATIONSHIPS BETWEEN HUMAN ACTIVITY AND MALARIA VECTORS IN URBAN AFRICA

This paper describes a geographic sampling strategy for ecologic studies and describes the relationship between human activities and anopheline larval ecology in urban areas. Kisumu and Malindi, Kenya were mapped using global positioning systems, and a geographic information system was used to overlay a measured grid, which served as a sampling frame. Grid cells were stratified and randomly selected according to levels of planning and drainage. A cross-sectional survey was conducted in April and May 2001 to collect entomologic and human ecologic data. Multivariate regression analysis was used to test the relationship between the abundance of potential larval habitats, and house density, socioeconomic status, and planning and drainage. In Kisumu, 98 aquatic habitats were identified, 65% of which were human made and 39% were positive for anopheline larvae. In Malindi, 91 aquatic habitats were identified, of which, 93% were human made and 65% were harboring anopheline larvae. The regression model explains 82% of the variance associated with the abundance of potential larval habitats in Kisumu. In Malindi, 59% of the variance was explained. As the number of households increased, the number of larval habitats increased correspondingly to a point. Beyond a critical threshold, the density of households appeared to suppress the development of aquatic habitats. The proportion of high-income households and the planning and drainage variables tested insignificant in both locations. The integration of social and biologic sciences will allow local mosquito and malaria control groups an opportunity to assess the risk of encountering potentially infectious mosquitoes in a given area, and concentrate resources accordingly.

Received March 25, 2002. Accepted for publication December 2, 2002.

Acknowledgments: We are grateful for the assistance of all scientific and technical staff at the Center for Geographic Medicine Research-Coast and the Kenya Medical Research Institute–Center for Vector Biology and Control Research (Kisian, Kenya), particularly Maurice Ombok, Richard Amimo, Francies Atieli, Nellie Njoki, Samuel Kahindi, Salim Omar, and Mtawali Chai. We also thank Allen High-tower (Centers for Disease Control and Prevention, Atlanta, GA) for his continued support of the field-based GPS/GIS teams in Kenya. This paper is published with the permission of the Director of the Kenya Medical Research Institute.

Financial support: This research was supported by National Science Foundation grant DEB-0083602 and National Institutes of Health grant U19 AI-45511.

Authors’ addresses: Joseph Keating and Kate Macintyre, Department of International Health and Development, TB46, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112-2699, Telephone: 504-988-8258, E-mail: jkeating{at}tulane.edu. Charles M. Mbogo and Lydiah Kibe, Centre for Geographic Medicine Research, Coast, Kenya Medical Research Institute, PO Box 428, Kilifi, Kenya. Andrew Githeko and Bryson Ndenga, Centre for Vector Biology and Control Research, Kenya Medical Research Institute, PO Box 1578, Kisumu, Kenya. James L. Regens, Institute for Science and Public Policy, Sarkeys Energy Center, University of Oklahoma, 100 E. Boyd Room 510, Norman, OK 73019-1006. Chris Swalm, Tulane University Health Sciences Center, SL18, 1430 Tulane Avenue, New Orleans, LA 70112-2699. Laura J. Steinberg, Department of Civil and Environmental Engineering, 206 Civil Engineering Building, Tulane University, New Orleans, LA 70118. John I. Githure, Human Health Division, International Centre of Insect Physiology and Ecology, PO Box 30772, Nairobi, Kenya. John C. Beier, Department of Tropical Medicine, School of Public Health and Tropical Medicine SL17, Tulane University, 1430 Tulane Avenue, New Orleans, LA 70112-2699.

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